Various computing systems can be used to communicate data including, for example, client-server systems. Users on the client side may access data stored on the server side. This access may generate traffic. There may be a desire to understand how relevant the data is to the users. One approach is to analyze the data and the traffic. But because the size and structure of the data and of the traffic may be large and complex, determining and presenting this relevancy may not be simple.
Consider the example of web sites. Many web sites are large and complex in nature and provide multiple functionalities, such as allowing users to find information, engage in commerce, socialize, or other functionalities. Such web sites may have thousands or even more of unique web pages and may be visited every day by millions or even more of users.
An administrator of a web site may be interested in determining traffic patterns associated with visits of the users to the web site. This understanding may allow the administrator to improve the design of the web site by ascertaining, for example, which web pages are most relevant to the users, which web pages are visited together, which web pages are most frequented, or other traffic pattern information. Accordingly, a summary of the traffic patterns may be generated and provided to the administrator. However, the size and structure of the web site and of the associated traffic may raise challenges when generating a meaningful summary that can properly communicate the various traffic patterns to the administrator. For example, communicating such a summary may lead either to overwhelming the administrator with too much information or to under-representing the traffic patterns with too little information.
There have been various efforts in the industry and academic research to generate and provide summaries of traffic patterns. However, the provided summaries may be limited in the level of available interaction and granularity. For example, Adobe Discover® and Google Analytics® offer analytics tools for summarizing traffic patterns of a web site. Although high level information may be provided, such summaries may not be granular enough to a level of individual web pages. Also, to be generated, the summaries may require a tagging of the web pages so that tags can be used for representing the traffic patterns. This tagging may present multiple challenges. For example, the tagging may be manual and, thus, may limit the applicability of the tools. In a further example, a same tag may be used for multiple web pages and, thus, information about traffic patterns between these web pages may be lost in the summary.